Examples illuminate data quality needs

Companies need to keep data quality high. Leaders likely hear this refrain often, possibly without thinking of what it really means to them. Simply learning about information management in abstract terms may lack the proper sense of urgency.

Smart Data Collective contributor Phil Simon recently gave a concrete example of what an informational error looks like in the world. In his case, it meant a delivery firm sent a palm tree to the wrong address, 60 miles from its actual destination. He noted that the same kind of small slip-up happens often in business.

He stated that instead of pointing fingers when something turns out looking wrong, companies should delve into the chain of actions that led to the current situation, checking to see where problems could have occurred. There could be a data quality lesson waiting at the end of the search.

CIO contributor Andy Hayler gave another easy to understand example of a project gone awry because of poor data understanding, this one much more costly than an out-of-place tree. He noted that a Mars mission failed because the scientists working on the spacecraft did not distinguish between centimeters and inches when making vital calculations.